Pragmatic Randomized Clinical Trials

Pragmatic Randomized Clinical Trials Using Primary Data Collection and Electronic Health Records addresses the practical aspects and challenges of the design, implementation, and dissemination of pragmatic randomized trials, also sometimes referred to as practical or hybrid randomized trials. While less restrictive and more generalizable than traditional randomized controlled trials, such trials have specific challenges which are addressed in this book. The book contains chapters encompassing common designs along with advantages and limitations of such designs, analytic aspects in planning trials and estimating sample size, and how to use patient partners to help design and operationalize pragmatic randomized trials. Pragmatic trials conducted using primary data collection and trials embedded in electronic health records - including electronic medical records and administrative insurance claims - are addressed. This comprehensive resource is valuable not only for pharmacoepidemiologists, biostatisticians and clinical researchers, but also across the biomedical field for those who are interested in applying pragmatic randomized clinical trials in their research. Addresses typical designs and challenges of pragmatic randomized clinical trials (pRCTs) Encompasses analytic aspects of such trials Discusses real cases on operational challenges in launching and conducting pRCTs in electronic health records

Pragmatic Randomized Clinical Trials Using Primary Data Collection and Electronic Health Records addresses the practical aspects and challenges of the design, implementation and dissemination of pragmatic randomized trials. The book contains chapters encompassing common designs, along with the advantages and limitations of such designs, analytic aspects in planning trials and estimating sample size, and how to use patient partners to help design and operationalize such trials. Pragmatic trials conducted using primary data collection and trials embedded in electronic health records - including electronic medical records and administrative insurance claims - are addressed. This comprehensive resource is valuable not only for biostatitians, but also for several members of biomedical field who are interested in applying pragmatic randomized clinical trials in their research. Brings typical designs and challenges of pragmatic randomized clinical trials (pRCTs) Encompasses analytic aspects for sample size determination of such trials Discusses real cases on operational challenges in launching and conducting pRCTs in electronic health records

This book begins with an introduction of pragmatic cluster randomized trials (PCTs) and reviews various pragmatic issues that need to be addressed by statisticians at the design stage. It discusses the advantages and disadvantages of each type of PCT, and provides sample size formulas, sensitivity analyses, and examples for sample size calculation. The generalized estimating equation (GEE) method will be employed to derive sample size formulas for various types of outcomes from the exponential family, including continuous, binary, and count variables. Experimental designs that have been frequently employed in PCTs will be discussed, including cluster randomized designs, matched-pair cluster randomized design, stratified cluster randomized design, stepped-wedge cluster randomized design, longitudinal cluster randomized design, and crossover cluster randomized design. It demonstrates that the GEE approach is flexible to accommodate pragmatic issues such as hierarchical correlation structures, different missing data patterns, randomly varying cluster sizes, etc. It has been reported that the GEE approach leads to under-estimated variance with limited numbers of clusters. The remedy for this limitation is investigated for the design of PCTs. This book can assist practitioners in the design of PCTs by providing a description of the advantages and disadvantages of various PCTs and sample size formulas that address various pragmatic issues, facilitating the proper implementation of PCTs to improve health care. It can also serve as a textbook for biostatistics students at the graduate level to enhance their knowledge or skill in clinical trial design. Key Features: Discuss the advantages and disadvantages of each type of PCTs, and provide sample size formulas, sensitivity analyses, and examples. Address an unmet need for guidance books on sample size calculations for PCTs; A wide variety of experimental designs adopted by PCTs are covered; The sample size solutions can be readily implemented due to the accommodation of common pragmatic issues encountered in real-world practice; Useful to both academic and industrial biostatisticians involved in clinical trial design; Can be used as a textbook for graduate students majoring in statistics and biostatistics.

Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.

Patient-reported outcomes (PROs) are measures of how patients feel or what they are able to do in the context of their health status; PROs are reports, usually on questionnaires, about a patient's health conditions, health behaviors, or experiences with health care that individuals report directly, without modification of responses by clinicians or others; thus, they directly reflect the voice of the patient. PROs cover domains such as physical health, mental and emotional health, functioning, symptoms and symptom burden, and health behaviors. They are relevant for many activities: helping patients and their clinicians make informed decisions about health care, monitoring the progress of care, setting policies for coverage and reimbursement of health services, improving the quality of health care services, and tracking or reporting on the performance of health care delivery organizations. We address the major methodological issues related to choosing, administering, and using PROs for these purposes, particularly in clinical practice settings. We include a framework for best practices in selecting PROs, focusing on choosing appropriate methods and modes for administering PRO measures to accommodate patients with diverse linguistic, cultural, educational, and functional skills, understanding measures developed through both classic and modern test theory, and addressing complex issues relating to scoring and analyzing PRO data.

America's health care system has become too complex and costly to continue business as usual. Best Care at Lower Cost explains that inefficiencies, an overwhelming amount of data, and other economic and quality barriers hinder progress in improving health and threaten the nation's economic stability and global competitiveness. According to this report, the knowledge and tools exist to put the health system on the right course to achieve continuous improvement and better quality care at a lower cost. The costs of the system's current inefficiency underscore the urgent need for a systemwide transformation. About 30 percent of health spending in 2009-roughly $750 billion-was wasted on unnecessary services, excessive administrative costs, fraud, and other problems. Moreover, inefficiencies cause needless suffering. By one estimate, roughly 75,000 deaths might have been averted in 2005 if every state had delivered care at the quality level of the best performing state. This report states that the way health care providers currently train, practice, and learn new information cannot keep pace with the flood of research discoveries and technological advances. About 75 million Americans have more than one chronic condition, requiring coordination among multiple specialists and therapies, which can increase the potential for miscommunication, misdiagnosis, potentially conflicting interventions, and dangerous drug interactions. Best Care at Lower Cost emphasizes that a better use of data is a critical element of a continuously improving health system, such as mobile technologies and electronic health records that offer significant potential to capture and share health data better. In order for this to occur, the National Coordinator for Health Information Technology, IT developers, and standard-setting organizations should ensure that these systems are robust and interoperable. Clinicians and care organizations should fully adopt these technologies, and patients should be encouraged to use tools, such as personal health information portals, to actively engage in their care. This book is a call to action that will guide health care providers; administrators; caregivers; policy makers; health professionals; federal, state, and local government agencies; private and public health organizations; and educational institutions.

This extensively revised second edition is a unique and portable handbook focusing on clinical trials in surgery. It includes new educational materials addressing the rapid evolution of novel research methodologies in basic science, clinical and educational research. The underlying principles of clinical trials, trial design, the development of a study cohort, statistics, data safety, data monitoring, and trial publication for device and drug trials are also discussed. Clinical Trials provides a comprehensive resource on clinical trials in surgery and describes all the stages of a clinical trial from generating a hypothesis through to trial publication and is a valuable resource for all practicing and trainee academic surgeons.

Nonpharmacological treatments include a wide variety of treatments such as surgery, technical procedures, implantable and non-implantable devices, rehabilitation, psychotherapy, and behavioral interventions. Unlike pharmacological treatments, these have no specific requirements for approval. Consequently, they can be widely proposed in clinical practice but may not have been adequately evaluated. This situation is an important barrier for the evaluation of the beneficial effects of these treatments and the conduct of clinical trials. Randomized Clinical Trials of Nonpharmacologic Treatments focuses on the methods for assessing nonpharmacological treatments, highlighting specific issues and trial design. Features: Chapters written by international experts in the field Highlights specific issues in assessing nonpharmacological treatments in trials including: how to overcome the difficulties of blinding patients, care providers, and outcome assessors the complexity of the intervention, the learning curve, and the clustering effect placebos that can be used issues of assessing harm and assessing the applicability of trials Presents a variety of trial designs for nonpharmacological treatments—including cluster randomized controlled trials, expertise-based trials, pragmatic trials, and nonrandomized trials. Provides several examples of the planning, conduct, analyses, and reporting of trials in different fields, including surgery, technical interventions, medical devices, rehabilitation, psychotherapy, and behavioral interventions. Providing practical examples that underline these issues and solutions, this book is one of the first to exclusively explore this topic, discussing various categories of treatments, from surgical procedures to psychotherapy.